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tlnagy/multibin_crispulator.ipynb

Created February 9, 2018 22:29
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Example of new multi-bin support in Crispulator
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multibin_crispulator.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"\u001b[1m\u001b[36mINFO: \u001b[39m\u001b[22m\u001b[36mLoading simulation framework\n",
"\u001b[39m"
]
}
],
"source": [
"include(joinpath(Pkg.dir(\"Crispulator\", \"src\", \"simulation\", \"load.jl\")))"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"FacsScreen <: ScreenSetup \n",
"\n",
" Number of genes: 250\n",
" Number of guides per gene: 5 (1250 guides total)\n",
" Cells per guide at transfection: 1000 (1250000 cells total)\n",
" Multiplicity of infection (M.O.I.): 0.25\n",
" Number of cells per guide at sequencing: 1000 (1250000 cells total)\n",
" \n",
" Number of cells per guide sorted: 1000 (1250000 cells total)\n",
" Gaussian standard deviation of sorting: 1.0 (phenotype units)\n",
" Bins:\n",
" Unsorted: 25-75 percentile of cells\n",
" GFP_low: 0-25 percentile of cells\n",
" GFP_high: 75-100 percentile of cells\n"
]
}
],
"source": [
"s = FacsScreen()\n",
"s.num_genes = 250\n",
"s.coverage = 5\n",
"s.representation = 1000\n",
"s.bottleneck_representation = 1000\n",
"s.seq_depth = 1000\n",
"s.bin_info = OrderedDict(:Unsorted => (0.25, 0.75), :GFP_low => (0.0, 0.25), :GFP_high => (0.75, 1.0))\n",
"println(s)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"max_phenotype_dists = Dict{Symbol, Tuple{Float64, Sampleable}}(\n",
" :inactive => (0.60, Delta(0.0)),\n",
" :negcontrol => (0.1, Delta(0.0)),\n",
" :increasing => (0.3, TruncatedNormal(0.1, 0.1, 0.025, 1)),\n",
");"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"lib = Library(max_phenotype_dists, CRISPRi())\n",
"guides, guide_freqs_dist = construct_library(s, lib);"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"cells, cell_phenotypes = transfect(s, lib, guides, guide_freqs_dist)\n",
"bin_cells = select(s, cells, cell_phenotypes, guides)\n",
"freqs = counts_to_freqs(bin_cells, length(guides));"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"raw_data = sequencing(Dict(:GFP_low=>s.seq_depth, :GFP_high=>s.seq_depth, :Unsorted=>s.seq_depth), guides, freqs)\n",
"guide_data, gene_data = differences_between_bins(raw_data);"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<table class=\"data-frame\"><thead><tr><th></th><th>gene</th><th>knockdown</th><th>theo_phenotype</th><th>behavior</th><th>class</th><th>initial_freq</th><th>barcodeid</th><th>counts_Unsorted</th><th>freqs_Unsorted</th><th>rel_freqs_Unsorted</th><th>counts_GFP_high</th><th>freqs_GFP_high</th><th>rel_freqs_GFP_high</th><th>log2fc_GFP_high_div_Unsorted</th><th>counts_GFP_low</th><th>freqs_GFP_low</th><th>rel_freqs_GFP_low</th><th>log2fc_GFP_low_div_Unsorted</th><th>log2fc_GFP_low_div_GFP_high</th></tr></thead><tbody><tr><th>1</th><td>1</td><td>0.8946520439455123</td><td>0.0</td><td>sigmoidal</td><td>inactive</td><td>0.0005012840267077555</td><td>1</td><td>643.5</td><td>0.0005145427286356822</td><td>0.89937106918239</td><td>619.5</td><td>0.0004953523238380809</td><td>0.880597014925373</td><td>-0.03043452258996548</td><td>702.5</td><td>0.0005617191404297851</td><td>0.994338287331918</td><td>0.14482028328031515</td><td>0.17525480587028064</td></tr><tr><th>2</th><td>1</td><td>0.9440468243098477</td><td>0.0</td><td>sigmoidal</td><td>inactive</td><td>0.002354391371340524</td><td>2</td><td>2906.5</td><td>0.002324037981009495</td><td>4.062194269741439</td><td>2953.5</td><td>0.0023616191904047975</td><td>4.198294243070362</td><td>0.047544046880958805</td><td>3035.5</td><td>0.0024271864067966016</td><td>4.2965322009908</td><td>0.08091347101159681</td><td>0.033369424130637745</td></tr><tr><th>3</th><td>1</td><td>0.8693232478376905</td><td>0.0</td><td>sigmoidal</td><td>inactive</td><td>0.0017257318952234207</td><td>3</td><td>2148.5</td><td>0.0017179410294852573</td><td>3.0027952480782667</td><td>1894.5</td><td>0.0015148425787106447</td><td>2.692963752665245</td><td>-0.157111293775095</td><td>2447.5</td><td>0.0019570214892553725</td><td>3.4642604387827323</td><td>0.20624128910984751</td><td>0.36335258288494265</td></tr><tr><th>4</th><td>1</td><td>0.8644691267563872</td><td>0.0</td><td>sigmoidal</td><td>inactive</td><td>0.0001807909604519774</td><td>4</td><td>241.5</td><td>0.00019310344827586207</td><td>0.33752620545073375</td><td>220.5</td><td>0.00017631184407796102</td><td>0.3134328358208955</td><td>-0.10684318978811783</td><td>178.5</td><td>0.0001427286356821589</td><td>0.2526539278131635</td><td>-0.4178369084139451</td><td>-0.31099371862582736</td></tr><tr><th>5</th><td>1</td><td>0.8819999446269764</td><td>0.0</td><td>sigmoidal</td><td>inactive</td><td>0.0008464304057524397</td><td>5</td><td>1143.5</td><td>0.0009143428285857072</td><td>1.5981830887491264</td><td>943.5</td><td>0.0007544227886056972</td><td>1.3411513859275053</td><td>-0.2529605993210921</td><td>1092.5</td><td>0.0008735632183908046</td><td>1.5463552724699223</td><td>-0.047560879630983335</td><td>0.20539971969010895</td></tr><tr><th>6</th><td>2</td><td>0.8344981605208943</td><td>0.035974427914806775</td><td>linear</td><td>increasing</td><td>0.0005752439650744736</td><td>6</td><td>770.5</td><td>0.0006160919540229885</td><td>1.0768693221523409</td><td>720.5</td><td>0.000576111944027986</td><td>1.0241648898365316</td><td>-0.07239518284990264</td><td>664.5</td><td>0.0005313343328335832</td><td>0.9405520169851381</td><td>-0.195263550845882</td><td>-0.12286836799597949</td></tr><tr><th>7</th><td>2</td><td>0.011987928377406448</td><td>0.0005167882754728696</td><td>linear</td><td>increasing</td><td>0.00043143297380585517</td><td>7</td><td>539.5</td><td>0.00043138430784607696</td><td>0.7540181691125087</td><td>508.5</td><td>0.0004065967016491754</td><td>0.7228144989339018</td><td>-0.06097384214038207</td><td>525.5</td><td>0.00042018990504747626</td><td>0.7438075017692852</td><td>-0.019669989133110105</td><td>0.041303853007272046</td></tr><tr><th>8</th><td>2</td><td>0.7802602404194776</td><td>0.03363628238106523</td><td>linear</td><td>increasing</td><td>0.0011422701592193117</td><td>8</td><td>1472.5</td><td>0.0011774112943528235</td><td>2.058001397624039</td><td>1435.5</td><td>0.0011478260869565216</td><td>2.040511727078891</td><td>-0.012312960020506466</td><td>1387.5</td><td>0.0011094452773613194</td><td>1.9639065817409769</td><td>-0.06751765620026375</td><td>-0.0552046961797572</td></tr><tr><th>9</th><td>2</td><td>0.9698836140152471</td><td>0.04181076700800011</td><td>linear</td><td>increasing</td><td>0.0010847457627118644</td><td>9</td><td>1264.5</td><td>0.0010110944527736132</td><td>1.7672955974842768</td><td>1432.5</td><td>0.0011454272863568216</td><td>2.036247334754797</td><td>0.20436944547116362</td><td>1328.5</td><td>0.0010622688655672163</td><td>1.8803963198867657</td><td>0.08949339721999643</td><td>-0.11487604825116704</td></tr><tr><th>10</th><td>2</td><td>0.9612451724888513</td><td>0.04143837194868252</td><td>linear</td><td>increasing</td><td>0.0006081150487930149</td><td>10</td><td>787.5</td><td>0.0006296851574212894</td><td>1.10062893081761</td><td>727.5</td><td>0.0005817091454272863</td><td>1.0341151385927505</td><td>-0.0899313319888599</td><td>753.5</td><td>0.0006024987506246877</td><td>1.0665251238499647</td><td>-0.04541020528408868</td><td>0.0445211267047713</td></tr><tr><th>11</th><td>3</td><td>0.7948390116041506</td><td>0.12714508710155592</td><td>linear</td><td>increasing</td><td>0.0006163328197226503</td><td>11</td><td>780.5</td><td>0.000624087956021989</td><td>1.0908455625436757</td><td>983.5</td><td>0.0007864067966016991</td><td>1.398009950248756</td><td>0.3579277637907561</td><td>646.5</td><td>0.0005169415292353823</td><td>0.9150743099787687</td><td>-0.2534860557749259</td><td>-0.6114138195656821</td></tr><tr><th>12</th><td>3</td><td>0.9257642849021502</td><td>0.14808832848030137</td><td>linear</td><td>increasing</td><td>0.0004273240883410375</td><td>12</td><td>523.5</td><td>0.0004185907046476762</td><td>0.7316561844863732</td><td>691.5</td><td>0.0005529235382308845</td><td>0.9829424307036246</td><td>0.42594105770982066</td><td>464.5</td><td>0.00037141429285357324</td><td>0.6574663835810334</td><td>-0.1542487341554268</td><td>-0.5801897918652474</td></tr><tr><th>13</th><td>3</td><td>0.9681973498627605</td><td>0.15487606242596444</td><td>linear</td><td>increasing</td><td>0.0008382126348228043</td><td>13</td><td>977.5</td><td>0.0007816091954022989</td><td>1.36617749825297</td><td>1223.5</td><td>0.0009783108445777112</td><td>1.7391613361762615</td><td>0.3482468373748099</td><td>931.5</td><td>0.0007448275862068966</td><td>1.318471337579618</td><td>-0.05127872686034848</td><td>-0.3995255642351585</td></tr><tr><th>14</th><td>3</td><td>0.8350298014385095</td><td>0.13357413927384013</td><td>linear</td><td>increasing</td><td>0.0010107858243451463</td><td>14</td><td>1344.5</td><td>0.0010750624687656171</td><td>1.8791055206149545</td><td>1410.5</td><td>0.0011278360819590204</td><td>2.004975124378109</td><td>0.09353825420283338</td><td>1078.5</td><td>0.0008623688155922039</td><td>1.526539278131635</td><td>-0.2997813723196906</td><td>-0.3933196265225237</td></tr><tr><th>15</th><td>3</td><td>0.12071086179122258</td><td>0.019309310203048328</td><td>linear</td><td>increasing</td><td>0.000842321520287622</td><td>15</td><td>1180.5</td><td>0.000943928035982009</td><td>1.6498951781970648</td><td>948.5</td><td>0.0007584207896051974</td><td>1.3482587064676617</td><td>-0.2912770193270318</td><td>978.5</td><td>0.0007824087956021989</td><td>1.3849964614295824</td><td>-0.2524920792091101</td><td>0.038784940117921725</td></tr><tr><th>16</th><td>4</td><td>0.8192552290607259</td><td>0.05398531740797401</td><td>linear</td><td>increasing</td><td>0.0003574730354391371</td><td>16</td><td>482.5</td><td>0.0003858070964517741</td><td>0.6743535988819007</td><td>371.5</td><td>0.00029705147426286856</td><td>0.5280739161336175</td><td>-0.35276538812671165</td><td>385.5</td><td>0.00030824587706146926</td><td>0.5456475583864119</td><td>-0.30553587584768005</td><td>0.047229512279031605</td></tr><tr><th>17</th><td>4</td><td>0.8466966521357885</td><td>0.05579358653129986</td><td>linear</td><td>increasing</td><td>0.0007889060092449923</td><td>17</td><td>965.5</td><td>0.0007720139930034982</td><td>1.3494060097833682</td><td>1121.5</td><td>0.000896751624187906</td><td>1.5941719971570716</td><td>0.24048279962575692</td><td>961.5</td><td>0.0007688155922038981</td><td>1.3609341825902337</td><td>0.012272804781975505</td><td>-0.2282099948437815</td></tr><tr><th>18</th><td>4</td><td>0.8696813072337897</td><td>0.05730817424092121</td><td>linear</td><td>increasing</td><td>0.0007395993836671802</td><td>18</td><td>946.5</td><td>0.0007568215892053973</td><td>1.3228511530398324</td><td>990.5</td><td>0.0007920039980009995</td><td>1.407960199004975</td><td>0.08995581267591622</td><td>857.5</td><td>0.0006856571714142928</td><td>1.2137296532200992</td><td>-0.12420362825080214</td><td>-0.21415944092671826</td></tr><tr><th>19</th><td>4</td><td>0.8342554963386333</td><td>0.05497376906684313</td><td>linear</td><td>increasing</td><td>0.0012408834103749358</td><td>19</td><td>1617.5</td><td>0.0012933533233383308</td><td>2.2606568832983926</td><td>1603.5</td><td>0.0012821589205397302</td><td>2.279317697228145</td><td>0.011859985051911812</td><td>1438.5</td><td>0.001150224887556222</td><td>2.0360934182590236</td><td>-0.15093828474785426</td><td>-0.1627982697997661</td></tr><tr><th>20</th><td>4</td><td>0.80274391659772</td><td>0.0528972945153285</td><td>linear</td><td>increasing</td><td>0.000965588084232152</td><td>20</td><td>1171.5</td><td>0.0009367316341829086</td><td>1.6373165618448637</td><td>1309.5</td><td>0.0010470764617691154</td><td>1.8614072494669507</td><td>0.18506044897759555</td><td>1216.5</td><td>0.0009727136431784108</td><td>1.7218683651804672</td><td>0.07264157246802207</td><td>-0.1124188765095734</td></tr><tr><th>21</th><td>5</td><td>0.982038239681068</td><td>0.1310606446012214</td><td>linear</td><td>increasing</td><td>0.0004601951720595788</td><td>21</td><td>574.5</td><td>0.0004593703148425787</td><td>0.8029350104821803</td><td>643.5</td><td>0.0005145427286356822</td><td>0.9147121535181236</td><td>0.18803459906472336</td><td>439.5</td><td>0.00035142428785607196</td><td>0.6220806794055203</td><td>-0.3681815211099807</td><td>-0.5562161201747041</td></tr><tr><th>22</th><td>5</td><td>0.8010932655468729</td><td>0.10691212981927088</td><td>linear</td><td>increasing</td><td>0.00020133538777606573</td><td>22</td><td>286.5</td><td>0.00022908545727136432</td><td>0.40041928721174</td><td>285.5</td><td>0.00022828585707146426</td><td>0.40582800284292814</td><td>0.019356950096072637</td><td>199.5</td><td>0.00015952023988005998</td><td>0.28237791932059453</td><td>-0.5038841861418304</td><td>-0.523241136237903</td></tr><tr><th>23</th><td>5</td><td>0.029979873000180384</td><td>0.004001047333698998</td><td>linear</td><td>increasing</td><td>0.0010847457627118644</td><td>23</td><td>1409.5</td><td>0.0011270364817591205</td><td>1.9699510831586304</td><td>1283.5</td><td>0.0010262868565717141</td><td>1.8244491826581377</td><td>-0.11069883850486874</td><td>1368.5</td><td>0.0010942528735632185</td><td>1.937013446567587</td><td>-0.024325836812736958</td><td>0.08637300169213173</td></tr><tr><th>24</th><td>5</td><td>0.9400161784637939</td><td>0.12545247354629735</td><td>linear</td><td>increasing</td><td>0.0008135593220338983</td><td>24</td><td>1043.5</td><td>0.0008343828085957022</td><td>1.4584206848357792</td><td>1100.5</td><td>0.000879960019990005</td><td>1.564321250888415</td><td>0.101129888221857</td><td>1011.5</td><td>0.0008087956021989005</td><td>1.4317055909412597</td><td>-0.02667207420882385</td><td>-0.12780196243068093</td></tr><tr><th>25</th><td>5</td><td>0.8470221872491343</td><td>0.11304170180629688</td><td>linear</td><td>increasing</td><td>0.00021366204417051874</td><td>25</td><td>320.5</td><td>0.000256271864067966</td><td>0.4479385045422781</td><td>269.5</td><td>0.00021549225387306346</td><td>0.3830845771144278</td><td>-0.22563774037610085</td><td>238.5</td><td>0.00019070464767616192</td><td>0.33757961783439494</td><td>-0.408072884220501</td><td>-0.18243514384440007</td></tr><tr><th>26</th><td>6</td><td>0.8467483124822435</td><td>0.0</td><td>linear</td><td>negcontrol</td><td>0.0009121725731895224</td><td>26</td><td>1169.5</td><td>0.0009351324337831085</td><td>1.6345213137665968</td><td>1018.5</td><td>0.0008143928035982009</td><td>1.4477611940298507</td><td>-0.1750445378964047</td><td>1192.5</td><td>0.0009535232383808096</td><td>1.6878980891719746</td><td>0.046359610933174575</td><td>0.2214041488295795</td></tr><tr><th>27</th><td>6</td><td>0.9714496206878338</td><td>0.0</td><td>linear</td><td>negcontrol</td><td>0.0004519774011299435</td><td>27</td><td>578.5</td><td>0.00046256871564217893</td><td>0.8085255066387143</td><td>574.5</td><td>0.0004593703148425787</td><td>0.8166311300639658</td><td>0.014391277028758094</td><td>528.5</td><td>0.00042258870564717643</td><td>0.7480537862703469</td><td>-0.11215128133207844</td><td>-0.1265425583608366</td></tr><tr><th>28</th><td>6</td><td>0.868834234180009</td><td>0.0</td><td>linear</td><td>negcontrol</td><td>0.0005752439650744736</td><td>28</td><td>737.5</td><td>0.0005897051474262868</td><td>1.0307477288609364</td><td>677.5</td><td>0.0005417291354322839</td><td>0.9630419331911869</td><td>-0.09802075940519697</td><td>747.5</td><td>0.0005977011494252873</td><td>1.0580325548478415</td><td>0.037692736341630007</td><td>0.1357134957468268</td></tr><tr><th>29</th><td>6</td><td>0.9632033120132345</td><td>0.0</td><td>linear</td><td>negcontrol</td><td>0.00011093990755007704</td><td>29</td><td>145.5</td><td>0.00011634182908545727</td><td>0.20335429769392033</td><td>132.5</td><td>0.00010594702648675662</td><td>0.18834399431414353</td><td>-0.1106254499675876</td><td>134.5</td><td>0.00010754622688655672</td><td>0.19037508846426043</td><td>-0.09515077395893135</td><td>0.015474676008656284</td></tr><tr><th>30</th><td>6</td><td>0.896319858875846</td><td>0.0</td><td>linear</td><td>negcontrol</td><td>0.0006944016435541859</td><td>30</td><td>860.5</td><td>0.000688055972013993</td><td>1.2026554856743534</td><td>778.5</td><td>0.0006224887556221889</td><td>1.1066098081023452</td><td>-0.12007680947103157</td><td>944.5</td><td>0.0007552223888055971</td><td>1.3368719037508847</td><td>0.15263781074089486</td><td>0.2727146202119265</td></tr><tr><th>&vellip;</th><td>&vellip;</td><td>&vellip;</td><td>&vellip;</td><td>&vellip;</td><td>&vellip;</td><td>&vellip;</td><td>&vellip;</td><td>&vellip;</td><td>&vellip;</td><td>&vellip;</td><td>&vellip;</td><td>&vellip;</td><td>&vellip;</td><td>&vellip;</td><td>&vellip;</td><td>&vellip;</td><td>&vellip;</td><td>&vellip;</td><td>&vellip;</td></tr></tbody></table>"
],
"text/plain": [
"1250×19 DataFrames.DataFrame\n",
"│ Row │ gene │ knockdown │ theo_phenotype │ behavior │ class │\n",
"├──────┼──────┼───────────┼────────────────┼───────────┼────────────┤\n",
"│ 1 │ 1 │ 0.894652 │ 0.0 │ sigmoidal │ inactive │\n",
"│ 2 │ 1 │ 0.944047 │ 0.0 │ sigmoidal │ inactive │\n",
"│ 3 │ 1 │ 0.869323 │ 0.0 │ sigmoidal │ inactive │\n",
"│ 4 │ 1 │ 0.864469 │ 0.0 │ sigmoidal │ inactive │\n",
"│ 5 │ 1 │ 0.882 │ 0.0 │ sigmoidal │ inactive │\n",
"│ 6 │ 2 │ 0.834498 │ 0.0359744 │ linear │ increasing │\n",
"│ 7 │ 2 │ 0.0119879 │ 0.000516788 │ linear │ increasing │\n",
"│ 8 │ 2 │ 0.78026 │ 0.0336363 │ linear │ increasing │\n",
"│ 9 │ 2 │ 0.969884 │ 0.0418108 │ linear │ increasing │\n",
"│ 10 │ 2 │ 0.961245 │ 0.0414384 │ linear │ increasing │\n",
"│ 11 │ 3 │ 0.794839 │ 0.127145 │ linear │ increasing │\n",
"⋮\n",
"│ 1239 │ 248 │ 0.938984 │ 0.22232 │ linear │ increasing │\n",
"│ 1240 │ 248 │ 0.881575 │ 0.208728 │ linear │ increasing │\n",
"│ 1241 │ 249 │ 0.899554 │ 0.0 │ linear │ inactive │\n",
"│ 1242 │ 249 │ 0.90624 │ 0.0 │ linear │ inactive │\n",
"│ 1243 │ 249 │ 0.947199 │ 0.0 │ linear │ inactive │\n",
"│ 1244 │ 249 │ 0.928829 │ 0.0 │ linear │ inactive │\n",
"│ 1245 │ 249 │ 0.941829 │ 0.0 │ linear │ inactive │\n",
"│ 1246 │ 250 │ 0.844685 │ 0.0 │ linear │ inactive │\n",
"│ 1247 │ 250 │ 0.690436 │ 0.0 │ linear │ inactive │\n",
"│ 1248 │ 250 │ 0.846888 │ 0.0 │ linear │ inactive │\n",
"│ 1249 │ 250 │ 0.792222 │ 0.0 │ linear │ inactive │\n",
"│ 1250 │ 250 │ 0.822388 │ 0.0 │ linear │ inactive │\n",
"\n",
"│ Row │ initial_freq │ barcodeid │ counts_Unsorted │ freqs_Unsorted │\n",
"├──────┼──────────────┼───────────┼─────────────────┼────────────────┤\n",
"│ 1 │ 0.000501284 │ 1 │ 643.5 │ 0.000514543 │\n",
"│ 2 │ 0.00235439 │ 2 │ 2906.5 │ 0.00232404 │\n",
"│ 3 │ 0.00172573 │ 3 │ 2148.5 │ 0.00171794 │\n",
"│ 4 │ 0.000180791 │ 4 │ 241.5 │ 0.000193103 │\n",
"│ 5 │ 0.00084643 │ 5 │ 1143.5 │ 0.000914343 │\n",
"│ 6 │ 0.000575244 │ 6 │ 770.5 │ 0.000616092 │\n",
"│ 7 │ 0.000431433 │ 7 │ 539.5 │ 0.000431384 │\n",
"│ 8 │ 0.00114227 │ 8 │ 1472.5 │ 0.00117741 │\n",
"│ 9 │ 0.00108475 │ 9 │ 1264.5 │ 0.00101109 │\n",
"│ 10 │ 0.000608115 │ 10 │ 787.5 │ 0.000629685 │\n",
"│ 11 │ 0.000616333 │ 11 │ 780.5 │ 0.000624088 │\n",
"⋮\n",
"│ 1239 │ 0.00125321 │ 1239 │ 1469.5 │ 0.00117501 │\n",
"│ 1240 │ 0.000636877 │ 1240 │ 826.5 │ 0.00066087 │\n",
"│ 1241 │ 0.000887519 │ 1241 │ 1071.5 │ 0.000856772 │\n",
"│ 1242 │ 0.000768362 │ 1242 │ 953.5 │ 0.000762419 │\n",
"│ 1243 │ 0.000653313 │ 1243 │ 857.5 │ 0.000685657 │\n",
"│ 1244 │ 0.000275295 │ 1244 │ 321.5 │ 0.000257071 │\n",
"│ 1245 │ 0.000267078 │ 1245 │ 315.5 │ 0.000252274 │\n",
"│ 1246 │ 0.000160247 │ 1246 │ 205.5 │ 0.000164318 │\n",
"│ 1247 │ 0.000312275 │ 1247 │ 425.5 │ 0.00034023 │\n",
"│ 1248 │ 0.000267078 │ 1248 │ 327.5 │ 0.000261869 │\n",
"│ 1249 │ 0.000488957 │ 1249 │ 632.5 │ 0.000505747 │\n",
"│ 1250 │ 0.00088341 │ 1250 │ 1050.5 │ 0.00083998 │\n",
"\n",
"│ Row │ rel_freqs_Unsorted │ counts_GFP_high │ freqs_GFP_high │\n",
"├──────┼────────────────────┼─────────────────┼────────────────┤\n",
"│ 1 │ 0.899371 │ 619.5 │ 0.000495352 │\n",
"│ 2 │ 4.06219 │ 2953.5 │ 0.00236162 │\n",
"│ 3 │ 3.0028 │ 1894.5 │ 0.00151484 │\n",
"│ 4 │ 0.337526 │ 220.5 │ 0.000176312 │\n",
"│ 5 │ 1.59818 │ 943.5 │ 0.000754423 │\n",
"│ 6 │ 1.07687 │ 720.5 │ 0.000576112 │\n",
"│ 7 │ 0.754018 │ 508.5 │ 0.000406597 │\n",
"│ 8 │ 2.058 │ 1435.5 │ 0.00114783 │\n",
"│ 9 │ 1.7673 │ 1432.5 │ 0.00114543 │\n",
"│ 10 │ 1.10063 │ 727.5 │ 0.000581709 │\n",
"│ 11 │ 1.09085 │ 983.5 │ 0.000786407 │\n",
"⋮\n",
"│ 1239 │ 2.05381 │ 2159.5 │ 0.00172674 │\n",
"│ 1240 │ 1.15514 │ 912.5 │ 0.000729635 │\n",
"│ 1241 │ 1.49755 │ 1152.5 │ 0.000921539 │\n",
"│ 1242 │ 1.33263 │ 913.5 │ 0.000730435 │\n",
"│ 1243 │ 1.19846 │ 890.5 │ 0.000712044 │\n",
"│ 1244 │ 0.449336 │ 377.5 │ 0.000301849 │\n",
"│ 1245 │ 0.44095 │ 293.5 │ 0.000234683 │\n",
"│ 1246 │ 0.287212 │ 160.5 │ 0.000128336 │\n",
"│ 1247 │ 0.594689 │ 334.5 │ 0.000267466 │\n",
"│ 1248 │ 0.457722 │ 313.5 │ 0.000250675 │\n",
"│ 1249 │ 0.883997 │ 566.5 │ 0.000452974 │\n",
"│ 1250 │ 1.4682 │ 1026.5 │ 0.00082079 │\n",
"\n",
"│ Row │ rel_freqs_GFP_high │ log2fc_GFP_high_div_Unsorted │ counts_GFP_low │\n",
"├──────┼────────────────────┼──────────────────────────────┼────────────────┤\n",
"│ 1 │ 0.880597 │ -0.0304345 │ 702.5 │\n",
"│ 2 │ 4.19829 │ 0.047544 │ 3035.5 │\n",
"│ 3 │ 2.69296 │ -0.157111 │ 2447.5 │\n",
"│ 4 │ 0.313433 │ -0.106843 │ 178.5 │\n",
"│ 5 │ 1.34115 │ -0.252961 │ 1092.5 │\n",
"│ 6 │ 1.02416 │ -0.0723952 │ 664.5 │\n",
"│ 7 │ 0.722814 │ -0.0609738 │ 525.5 │\n",
"│ 8 │ 2.04051 │ -0.012313 │ 1387.5 │\n",
"│ 9 │ 2.03625 │ 0.204369 │ 1328.5 │\n",
"│ 10 │ 1.03412 │ -0.0899313 │ 753.5 │\n",
"│ 11 │ 1.39801 │ 0.357928 │ 646.5 │\n",
"⋮\n",
"│ 1239 │ 3.06965 │ 0.579773 │ 1189.5 │\n",
"│ 1240 │ 1.29709 │ 0.167211 │ 494.5 │\n",
"│ 1241 │ 1.63824 │ 0.129536 │ 1111.5 │\n",
"│ 1242 │ 1.29851 │ -0.0374269 │ 1123.5 │\n",
"│ 1243 │ 1.26581 │ 0.0788803 │ 803.5 │\n",
"│ 1244 │ 0.536603 │ 0.256059 │ 388.5 │\n",
"│ 1245 │ 0.4172 │ -0.0798782 │ 364.5 │\n",
"│ 1246 │ 0.228145 │ -0.332164 │ 249.5 │\n",
"│ 1247 │ 0.47548 │ -0.322752 │ 424.5 │\n",
"│ 1248 │ 0.445629 │ -0.0386281 │ 386.5 │\n",
"│ 1249 │ 0.805259 │ -0.134588 │ 542.5 │\n",
"│ 1250 │ 1.45913 │ -0.00894119 │ 1261.5 │\n",
"\n",
"│ Row │ freqs_GFP_low │ rel_freqs_GFP_low │ log2fc_GFP_low_div_Unsorted │\n",
"├──────┼───────────────┼───────────────────┼─────────────────────────────┤\n",
"│ 1 │ 0.000561719 │ 0.994338 │ 0.14482 │\n",
"│ 2 │ 0.00242719 │ 4.29653 │ 0.0809135 │\n",
"│ 3 │ 0.00195702 │ 3.46426 │ 0.206241 │\n",
"│ 4 │ 0.000142729 │ 0.252654 │ -0.417837 │\n",
"│ 5 │ 0.000873563 │ 1.54636 │ -0.0475609 │\n",
"│ 6 │ 0.000531334 │ 0.940552 │ -0.195264 │\n",
"│ 7 │ 0.00042019 │ 0.743808 │ -0.01967 │\n",
"│ 8 │ 0.00110945 │ 1.96391 │ -0.0675177 │\n",
"│ 9 │ 0.00106227 │ 1.8804 │ 0.0894934 │\n",
"│ 10 │ 0.000602499 │ 1.06653 │ -0.0454102 │\n",
"│ 11 │ 0.000516942 │ 0.915074 │ -0.253486 │\n",
"⋮\n",
"│ 1239 │ 0.000951124 │ 1.68365 │ -0.286708 │\n",
"│ 1240 │ 0.000395402 │ 0.699929 │ -0.722782 │\n",
"│ 1241 │ 0.000888756 │ 1.57325 │ 0.0711383 │\n",
"│ 1242 │ 0.000898351 │ 1.59023 │ 0.254957 │\n",
"│ 1243 │ 0.000642479 │ 1.1373 │ -0.0755764 │\n",
"│ 1244 │ 0.000310645 │ 0.549894 │ 0.291358 │\n",
"│ 1245 │ 0.000291454 │ 0.515924 │ 0.226541 │\n",
"│ 1246 │ 0.0001995 │ 0.353149 │ 0.298164 │\n",
"│ 1247 │ 0.00033943 │ 0.600849 │ 0.0148676 │\n",
"│ 1248 │ 0.000309045 │ 0.547063 │ 0.257236 │\n",
"│ 1249 │ 0.000433783 │ 0.76787 │ -0.20318 │\n",
"│ 1250 │ 0.0010087 │ 1.78556 │ 0.282326 │\n",
"\n",
"│ Row │ log2fc_GFP_low_div_GFP_high │\n",
"├──────┼─────────────────────────────┤\n",
"│ 1 │ 0.175255 │\n",
"│ 2 │ 0.0333694 │\n",
"│ 3 │ 0.363353 │\n",
"│ 4 │ -0.310994 │\n",
"│ 5 │ 0.2054 │\n",
"│ 6 │ -0.122868 │\n",
"│ 7 │ 0.0413039 │\n",
"│ 8 │ -0.0552047 │\n",
"│ 9 │ -0.114876 │\n",
"│ 10 │ 0.0445211 │\n",
"│ 11 │ -0.611414 │\n",
"⋮\n",
"│ 1239 │ -0.866481 │\n",
"│ 1240 │ -0.889993 │\n",
"│ 1241 │ -0.0583979 │\n",
"│ 1242 │ 0.292384 │\n",
"│ 1243 │ -0.154457 │\n",
"│ 1244 │ 0.0352988 │\n",
"│ 1245 │ 0.306419 │\n",
"│ 1246 │ 0.630327 │\n",
"│ 1247 │ 0.337619 │\n",
"│ 1248 │ 0.295864 │\n",
"│ 1249 │ -0.068592 │\n",
"│ 1250 │ 0.291267 │"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"guide_data"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
"anaconda-cloud": {},
"kernelspec": {
"display_name": "Julia 0.6.1",
"language": "julia",
"name": "julia-0.6"
},
"language_info": {
"file_extension": ".jl",
"mimetype": "application/julia",
"name": "julia",
"version": "0.6.1"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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